From a45e203ad0935c30c6c1050f621e01187ecdd41e Mon Sep 17 00:00:00 2001
From: AdamRashid96 <71362382+AdamRashid96@users.noreply.github.com>
Date: Thu, 22 Feb 2024 15:05:01 -0800
Subject: [PATCH] Eval table (#134)

* table

* test table

* tables

* eval description

* readme
---
 README.md                  |   4 +
 docs/source/tests/eval.rst | 305 +++++++++++++++++++++++++++++++++++++
 2 files changed, 309 insertions(+)
 create mode 100644 docs/source/tests/eval.rst

diff --git a/README.md b/README.md
index b41abfbeb..aa16bf6b1 100644
--- a/README.md
+++ b/README.md
@@ -13,6 +13,10 @@ for Real-Time Radiance Field Rendering
 
 ![Teaser](/docs/source/imgs/training.gif?raw=true)
 
+## Evaluation
+A full evalaution of Nerfstudio's implementation of Gaussian Splatting against the original Inria method can be found [here](https://docs.gsplat.studio/tests/eval.html).
+
+
 ## Installation
 
 **Dependence**: Please install [Pytorch](https://pytorch.org/get-started/locally/) first.
diff --git a/docs/source/tests/eval.rst b/docs/source/tests/eval.rst
new file mode 100644
index 000000000..73a532e85
--- /dev/null
+++ b/docs/source/tests/eval.rst
@@ -0,0 +1,305 @@
+Evaluation
+===================================
+
+We evaluate our implementation of Gaussian Splatting (`Splatfacto <https://github.com/nerfstudio-project/nerfstudio/tree/1d070f5625ab42d0a0dff1ad4c6cfb655aab6d3d>`_) on the Mip-NeRF 360 dataset, benchmarking it against the original `Inria <https://github.com/graphdeco-inria/gaussian-splatting/tree/2eee0e26d2d5fd00ec462df47752223952f6bf4e>`_ method. We evaluate all methods with the same resolution (2x downscale) and COLMAP params/undistortion, and we report results at 7,000 and 30,000 steps. All evaluations were executed on an NVIDIA RTX 4090 GPU.
+
+.. list-table:: **Time**
+   :widths: 10 10 10 10 10 10 10 10 10 10
+   :header-rows: 1
+
+   * - 
+     - Bicycle
+     - Bonsai
+     - Counter
+     - Flowers
+     - Garden
+     - Kitchen
+     - Stump
+     - Treehill
+     - Avg
+   * - inria-7k
+     - 3:34
+     - 3:27
+     - 3:05
+     - 3:02
+     - 3:51
+     - 4:00
+     - 3:25
+     - 2:53
+     - 3:24
+   * - splfacto-7k
+     - 2:36
+     - 2:18
+     - 2:06
+     - 2:14
+     - 2:49
+     - 2:17
+     - 2:24
+     - 2:23
+     - 2:23
+   * - splfacto-big-7k
+     - 3:41
+     - 3:11
+     - 2:59
+     - 2:51
+     - 3:51
+     - 3:15
+     - 2:49
+     - 2:47
+     - 3:10
+   * - inria-30k
+     - 25:07
+     - 14:37
+     - 15:24
+     - 17:32
+     - 24:03
+     - 19:02
+     - 20:25
+     - 18:02
+     - 19:17
+   * - splfacto-30k
+     - 18:03
+     - 10:13
+     - 9:07
+     - 13:25
+     - 14:58
+     - 10:02
+     - 15:15
+     - 16:56
+     - 13:30
+   * - splfacto-big-30k
+     - 31:05
+     - 13:32
+     - 13:27
+     - 22:44
+     - 26:03
+     - 16:16
+     - 21:58
+     - 25:26
+     - 21:19
+
+.. list-table:: **PSNR**
+   :widths: 10 10 10 10 10 10 10 10 10 10
+   :header-rows: 1
+
+   * - 
+     - Bicycle
+     - Bonsai
+     - Counter
+     - Flowers
+     - Garden
+     - Kitchen
+     - Stump
+     - Treehill
+     - Avg
+   * - inria-7k
+     - 24.11
+     - 29.49
+     - 27.16
+     - 20.54
+     - 26.53
+     - 29.02
+     - 26.74
+     - 22.50
+     - 25.76
+   * - splatfacto-7k
+     - 22.99
+     - 29.45
+     - 26.92
+     - 20.33
+     - 25.76
+     - 28.48
+     - 24.59
+     - 21.91
+     - 25.05
+   * - splatfacto-big-7k
+     - 23.66
+     - 29.69
+     - 27.01
+     - 20.73
+     - 26.58
+     - 28.82
+     - 25.69
+     - 22.11
+     - 25.54
+   * - inria-30k
+     - 25.61
+     - 31.89
+     - 28.96
+     - 21.56
+     - 27.60
+     - 31.30
+     - 25.89
+     - 22.07
+     - 26.86
+   * - splatfacto-30k
+     - 24.99
+     - 32.14
+     - 28.72
+     - 21.54
+     - 27.31
+     - 31.18
+     - 25.64
+     - 22.28
+     - 26.73
+   * - splatfacto-big-30k
+     - 25.7
+     - 32.23
+     - 28.95
+     - 21.96
+     - 27.83
+     - 31.6
+     - 26.7
+     - 22.38
+     - 27.17
+
+
+.. list-table:: **LPIPS**
+   :widths: 10 10 10 10 10 10 10 10 10 10
+   :header-rows: 1
+
+   * - 
+     - Bicycle
+     - Bonsai
+     - Counter
+     - Flowers
+     - Garden
+     - Kitchen
+     - Stump
+     - Treehill
+     - Avg
+   * - inria-7k
+     - 0.31
+     - 0.24
+     - 0.25
+     - 0.42
+     - 0.16
+     - 0.16
+     - 0.28
+     - 0.42
+     - 0.28
+   * - splfacto-7k
+     - 0.31
+     - 0.16
+     - 0.21
+     - 0.44
+     - 0.15
+     - 0.14
+     - 0.28
+     - 0.45
+     - 0.27
+   * - splfacto-big-7k
+     - 0.28
+     - 0.16
+     - 0.20
+     - 0.42
+     - 0.12
+     - 0.13
+     - 0.23
+     - 0.43
+     - 0.24
+   * - inria-30k
+     - 0.21
+     - 0.21
+     - 0.20
+     - 0.34
+     - 0.11
+     - 0.13
+     - 0.22
+     - 0.32
+     - 0.22
+   * - splfacto-30k
+     - 0.18
+     - 0.13
+     - 0.17
+     - 0.34
+     - 0.09
+     - 0.10
+     - 0.18
+     - 0.32
+     - 0.19
+   * - splfacto-big-30k
+     - 0.15
+     - 0.13
+     - 0.15
+     - 0.31
+     - 0.07
+     - 0.09
+     - 0.15
+     - 0.28
+     - 0.17
+
+.. list-table:: **SSIM**
+   :widths: 10 10 10 10 10 10 10 10 10 10
+   :header-rows: 1
+
+   * - 
+     - Bicycle
+     - Bonsai
+     - Counter
+     - Flowers
+     - Garden
+     - Kitchen
+     - Stump
+     - Treehill
+     - Avg
+   * - inria-7k
+     - 0.69
+     - 0.92
+     - 0.88
+     - 0.53
+     - 0.83
+     - 0.90
+     - 0.73
+     - 0.59
+     - 0.76
+   * - splfacto-7k
+     - 0.65
+     - 0.92
+     - 0.88
+     - 0.53
+     - 0.85
+     - 0.90
+     - 0.68
+     - 0.58
+     - 0.74
+   * - splfacto-big-7k
+     - 0.69
+     - 0.92
+     - 0.88
+     - 0.55
+     - 0.84
+     - 0.90
+     - 0.74
+     - 0.61
+     - 0.77
+   * - inria-30k
+     - 0.78
+     - 0.94
+     - 0.91
+     - 0.61
+     - 0.87
+     - 0.92
+     - 0.77
+     - 0.63
+     - 0.80
+   * - splfacto-30k
+     - 0.75
+     - 0.94
+     - 0.90
+     - 0.60
+     - 0.85
+     - 0.92
+     - 0.73
+     - 0.63
+     - 0.79
+   * - splfacto-big-30k
+     - 0.78
+     - 0.94
+     - 0.91
+     - 0.63
+     - 0.88
+     - 0.93
+     - 0.77
+     - 0.64
+     - 0.81